Boxplot

Boxplot

The Boxplot node creates box-and-whisker plots using ggplot2 to help you compare the distribution of a numeric variable across groups.

What it does

• Creates a boxplot from a grouping variable (X) and a numeric value variable (Y)
• Optionally overlays jittered data points from the original observations
• Optionally fill boxes by a second grouping variable
• Supports custom axis labels
• The plot can be downloaded as a PNG image

How to use it

1. Connect a data source — drag an edge from an Input CSV node
2. Select a grouping variable (X) — choose the categorical column for the x axis
3. Select a value variable (Y) — choose the numeric column to compare across groups
4. Optionally configure — enable Add data points, set a fill variable, or set custom axis labels
5. Click Run — the boxplot is generated and displayed

Configuration

Setting	Required	Description
Upstream connection	Yes	A node providing data
Grouping variable (X)	Yes	Categorical variable for the x axis
Value variable (Y)	Yes	Numeric variable for the y axis
Add data points	No	Overlays jittered points (geom_point(position = "jitter")) on top of the boxplot
Fill variable	No	A second grouping variable to fill boxes by
X axis label	No	Custom label (defaults to column name)
Y axis label	No	Custom label (defaults to column name)
Comment	No	Annotation for generated R code

Output

The Output tab displays:

• The boxplot as an image
• A Zoom button to view the plot full-screen
• A Download plot button to save it as a PNG file (named boxplot_{y}_by_{x}.png)

Generated R code

Basic boxplot:

library(ggplot2)
ggplot(data = my_data, aes(x = species, y = weight)) +
  geom_boxplot() +
  theme_classic()

With fill variable and custom labels:

library(ggplot2)
ggplot(data = my_data, aes(x = species, y = weight, fill = diet)) +
  geom_boxplot() +
  theme_classic() +
  labs(x = "Species", y = "Weight (kg)")

With jittered data points:

library(ggplot2)
ggplot(data = my_data, aes(x = species, y = weight)) +
  geom_boxplot() +
  geom_point(position = "jitter") +
  theme_classic()

Tips

• The grouping variable (X) is typically categorical — it defines the groups along the x axis
• The value variable (Y) should be numeric — it defines the distribution shown in each box
• Enable Add data points when you want to show individual observations alongside summary distribution
• Use the fill variable to add a second level of grouping within each x category
• The box shows the interquartile range (IQR), the line inside is the median, and whiskers extend to 1.5 × IQR
• Points beyond the whiskers are shown as outliers
• You can download the plot for use in reports or presentations